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Honeycomb

byHoneycomb
in
4.7

Overview

Product Information on Honeycomb

Updated 13th October 2025

What is Honeycomb?

Honeycomb is a software designed for observability and analysis of complex systems. It provides tools for real-time event-based data collection, enabling users to visualize and explore system behavior across distributed environments. The software helps teams monitor application performance, identify bottlenecks, and troubleshoot issues by aggregating telemetry data such as logs and traces. Honeycomb offers querying capabilities to surface patterns and anomalies, allowing users to drill down into high-cardinality datasets. The software supports integration with various platforms and cloud environments, making it suitable for organizations seeking to improve reliability and maintainability of their applications by gaining deeper insight into production systems.

Honeycomb Pricing

Honeycomb software uses a usage-based pricing model where customers are charged based on the volume of data events analyzed per month. The software offers multiple plans that vary by features such as retention period, number of team members, and support options. A free tier with limited volume is also available and enterprise plans can be customized based on specific requirements and event volume.

Overall experience with Honeycomb

Chief Information Officer
30B + USD, Insurance (except health)
FAVORABLE

“This is not an observability conversation. It's an engineering culture conversation.”

4.0
Mar 25, 2026
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.
Software Developer
<50M USD, Software
CRITICAL

“Good enough, some strengths, clunky”

3.0
Apr 29, 2026
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.

About Company

Company Description

Updated 7th December 2023

Honeycomb is an organization engaged in offering full stack observability. Established based on prior experiences faced while resolving issues at the scale of millions of applications serving a large user base, the company's focus is on high cardinality data and collaborative problem solving. Honeycomb's primary business solution involves enabling every engineer to instrument and observe the behavior of their system, thereby assisting in a comprehensive understanding and debugging of production software.

Company Details

Updated 26th February 2025
Company type
Private
Year Founded
2016
Head office location
San Francisco, United States
Number of employees
51 - 200
Website
https://www.honeycomb.io

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

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Peer Discussions

Honeycomb Reviews and Ratings

4.7

(109 Ratings)

Rating Distribution

5 Star
72%
4 Star
27%
3 Star
2%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?
  • Chief Information Officer
    10B+ USD
    Insurance (except health)
    Review Source

    This is not an observability conversation. It's an engineering culture conversation.

    4.0
    Mar 25, 2026
    We brought Honeycomb into our Group function as part of our broader engineering transformation programme. We were not evaluating monitoring tools. We have plenty of those. What we needed was a forcing function to change how engineering teams understood the production systems they were responsible for but had limited visibility into. Honeycomb delivered on that. The high cardinality query engine gave individual service teams within our business units direct, self-service access to their own production telemetry for the first time within our company. In an environment where most teams operated through borrowed visibility, relying on infrastructure dashboards owned by other teams or vendor managed alerting that they could not customize, during incidents, Honeycomb platform shifted the engineering behavior to effectively test application behavior in pre-production. That was a first for us. What held us back from a perfect score: the SaaS only model created real friction during procurement for a European regulated insurer. Data residency, audit trail requirements, and third party risk assessment added months. And the product assumes an engineering-led organization. In outsourcing-heavy enterprises such as ours, the onboarding investment is steeper and that was a learning for Honeycomb. Both of these are solvable, but they are real.
  • Chief Information Officer
    10B+ USD
    Insurance (except health)
    Review Source

    This is not an observability conversation. It's an engineering culture conversation.

    4.0
    Mar 25, 2026
    We brought Honeycomb into our Group function as part of our broader engineering transformation programme. We were not evaluating monitoring tools. We have plenty of those. What we needed was a forcing function to change how engineering teams understood the production systems they were responsible for but had limited visibility into. Honeycomb delivered on that. The high cardinality query engine gave individual service teams within our business units direct, self-service access to their own production telemetry for the first time within our company. In an environment where most teams operated through borrowed visibility, relying on infrastructure dashboards owned by other teams or vendor managed alerting that they could not customize, during incidents, Honeycomb platform shifted the engineering behavior to effectively test application behavior in pre-production. That was a first for us. What held us back from a perfect score: the SaaS only model created real friction during procurement for a European regulated insurer. Data residency, audit trail requirements, and third party risk assessment added months. And the product assumes an engineering-led organization. In outsourcing-heavy enterprises such as ours, the onboarding investment is steeper and that was a learning for Honeycomb. Both of these are solvable, but they are real.
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User Sentiment About Honeycomb
Reviewer Insights for: Honeycomb
Deciding Factors: Honeycomb Vs. Market Average
Performance of Honeycomb Across Market Features

Honeycomb Likes & Dislikes

Like

1. The query engine and the UX are the real differentiators from a user perspective. High cardinality exploration across traces and events lets you ask questions about production that no existing monitoring tools at our disposal can answer. When an incident involves a combination of customer segment, deployment version, and infrastructure region, using the span attribute feature is such a powerful way for teams to correlate the various subsystems across a landscape as complex as ours. None of the existing monitoring tools allow us to enrich tracing data on the fly. This is not an incremental improvement over APM tooling. It's a step change in understanding production systems. 2. OTel-native instrumentation is non-negotiable for us, both ingest and export. We were consolidating a fragmented observability stack across multiple vendors and needed portable instrumentation to support our telemetry pipelines. Honeycombs commitment to OpenTelemetry meant we could invest in instrumentation once and not face re-work if our vendor landscape evolved. In a regulated environment where vendor changes require long procurement cycles, portability is strategic and necessary. 3. Unlike other vendors, the team engaged as a strategic partner, not a product vendor. Honeycombs willingness to discuss engineering culture change and how observability practice actually scales inside large regulated enterprises was unmatched by any vendor conversation I've had at our company on the buyer side. Product leadership engaged directly with our architecture team on strategic questions.

Like

1. The query engine and the UX are the real differentiators from a user perspective. High cardinality exploration across traces and events lets you ask questions about production that no existing monitoring tools at our disposal can answer. When an incident involves a combination of customer segment, deployment version, and infrastructure region, using the span attribute feature is such a powerful way for teams to correlate the various subsystems across a landscape as complex as ours. None of the existing monitoring tools allow us to enrich tracing data on the fly. This is not an incremental improvement over APM tooling. It's a step change in understanding production systems. 2. OTel-native instrumentation is non-negotiable for us, both ingest and export. We were consolidating a fragmented observability stack across multiple vendors and needed portable instrumentation to support our telemetry pipelines. Honeycombs commitment to OpenTelemetry meant we could invest in instrumentation once and not face re-work if our vendor landscape evolved. In a regulated environment where vendor changes require long procurement cycles, portability is strategic and necessary. 3. Unlike other vendors, the team engaged as a strategic partner, not a product vendor. Honeycombs willingness to discuss engineering culture change and how observability practice actually scales inside large regulated enterprises was unmatched by any vendor conversation I've had at our company on the buyer side. Product leadership engaged directly with our architecture team on strategic questions.

Like

1. The query engine and the UX are the real differentiators from a user perspective. High cardinality exploration across traces and events lets you ask questions about production that no existing monitoring tools at our disposal can answer. When an incident involves a combination of customer segment, deployment version, and infrastructure region, using the span attribute feature is such a powerful way for teams to correlate the various subsystems across a landscape as complex as ours. None of the existing monitoring tools allow us to enrich tracing data on the fly. This is not an incremental improvement over APM tooling. It's a step change in understanding production systems. 2. OTel-native instrumentation is non-negotiable for us, both ingest and export. We were consolidating a fragmented observability stack across multiple vendors and needed portable instrumentation to support our telemetry pipelines. Honeycombs commitment to OpenTelemetry meant we could invest in instrumentation once and not face re-work if our vendor landscape evolved. In a regulated environment where vendor changes require long procurement cycles, portability is strategic and necessary. 3. Unlike other vendors, the team engaged as a strategic partner, not a product vendor. Honeycombs willingness to discuss engineering culture change and how observability practice actually scales inside large regulated enterprises was unmatched by any vendor conversation I've had at our company on the buyer side. Product leadership engaged directly with our architecture team on strategic questions.

Dislike

The dashboarding works fine, but is clunky and generally unpleasant. I prefer the visual and experience of building a dashboard in other products from years ago. Need more flexibility in how I layout the board itself/compactness; unbelievable there isn't already a collapsible row/sections feature. Cloning boards between environments doesn't include text panels, but that's a known limitation. Managing board definitions in code/terrafrom is painful, why can't I just export/import from JSON? Can't create a board that includes an attribute until that attribute has been seen in that environment. The separation of datasets is pretty strict; so combining observability data from different systems basically has to be handled outside the system. Alerting works, but has various limits (how much history can be queried) that make it a little harder to use.

Dislike

The dashboarding works fine, but is clunky and generally unpleasant. I prefer the visual and experience of building a dashboard in other products from years ago. Need more flexibility in how I layout the board itself/compactness; unbelievable there isn't already a collapsible row/sections feature. Cloning boards between environments doesn't include text panels, but that's a known limitation. Managing board definitions in code/terrafrom is painful, why can't I just export/import from JSON? Can't create a board that includes an attribute until that attribute has been seen in that environment. The separation of datasets is pretty strict; so combining observability data from different systems basically has to be handled outside the system. Alerting works, but has various limits (how much history can be queried) that make it a little harder to use.

Dislike

The dashboarding works fine, but is clunky and generally unpleasant. I prefer the visual and experience of building a dashboard in other products from years ago. Need more flexibility in how I layout the board itself/compactness; unbelievable there isn't already a collapsible row/sections feature. Cloning boards between environments doesn't include text panels, but that's a known limitation. Managing board definitions in code/terrafrom is painful, why can't I just export/import from JSON? Can't create a board that includes an attribute until that attribute has been seen in that environment. The separation of datasets is pretty strict; so combining observability data from different systems basically has to be handled outside the system. Alerting works, but has various limits (how much history can be queried) that make it a little harder to use.